About Impact Analytics
Impact Analytics is an agentic-first AI software company redefining the future of retail merchandising through cutting-edge AI innovation. As one of the fastest-growing companies in the retail AI space, Impact Analytics has built a strong global presence, with its solutions deployed across five continents.
Backed as a Series D company, Impact Analytics is at the forefront of leveraging the latest advancements in LLMs, Generative AI, and Agentic AI to transform how retailers make decisions. Beyond building industry-leading merchandising software, the company is focused on developing foundational AI-driven platforms and intelligent agents that will fundamentally reshape retail operations and merchandising workflows.
What truly sets Impact apart is the combination of deep domain expertise and a strong culture of innovation. It is one of the few India-born AI companies that has successfully established a significant global footprint in enterprise retail software. The company’s growth and innovation have been recognized by leading global platforms and institutions such as Fortune, Gartner, and the Inc. 5000.
For candidates who are excited about building next-generation AI products, solving complex real-world problems, and being part of a high-growth global technology company, Impact Analytics offers an exceptional opportunity to create meaningful impact at scale.
The impact that you will be making:
- We are building AI-native enterprise SaaS products that put agentic systems into the hands of business users. The work spans two problem areas.
- A natural language analytics assistant that converts user questions into SQL against analytical databases, surfaces insight, and explains decisions in plain English.
- A no-code platform for deploying enterprise multi-agent workflows, orchestrating LLM-powered agents with durable state, human approval gates, and observability built in.
- As a Senior AI Engineer, you own the design and delivery of these systems end-to-end. You write production code, make sound architectural calls independently, and go deep on hard problems without needing to be pointed at them.
What You'll Build
- Multi-agent orchestration with LangGraph: state machines, interrupt-before-commit approval flows, and durable checkpointing
- NL-to-SQL pipelines with semantic layer design, translating user intent into safe, multi-tenant analytical queries
- RAG systems with retrieval pipelines, reranking, and context management tuned for enterprise data
- Building and consuming MCP servers to connect LLMs to internal analytical systems
- Evaluation infrastructure to measure response quality, agent trajectory, and regression across model updates
Must Have
- Engineering Foundations
- Production-grade Python: APIs, services, and libraries, not just scripts
- FastAPI for scalable, documented, async APIs
- LangGraph for stateful agentic workflows: shipped something with it, not just prototyped
- NL-to-SQL or text-to-SQL: translating natural language to structured queries against real schemas
- OLAP databases (ClickHouse, BigQuery, or equivalent): query design, partitioning, performance optimization
- Multi-tenant data architecture: query isolation, row-level security, schema design for enterprise SaaS
- AI/LLM Engineering
- RAG fundamentals: chunking strategies, embedding models, BM25/hybrid retrieval, cross-encoder reranking, GraphRAG
- Agentic patterns: ReAct, Self-RAG, CRAG, state machines, human-in-the-loop interrupts
- Evaluation: RAGAS, LLM-as-Judge, trajectory evaluation; you know what good looks like and how to measure it
- Semantic layer design: intent mapping, entity resolution, context management for analytics chat
Good to Have
- Vector databases: indexing, retrieval, and the tradeoffs (Cosine similarity, HNSW, IVF, ANN)
- Langfuse, LangSmith, or equivalent observability: tracing, cost tracking, failure analysis in production
- LangGraph Studio for local agent debugging
- CrewAI or other multi-agent orchestration frameworks
- DuckDB for local/embedded analytical workloads
- Domain exposure in data-intensive enterprise verticals (planning, operations, finance, or similar)
What we offer
- An opportunity to be part of some of the best enterprise SaaS products to be built out of India
- Opportunities to quench your thirst for problem-solving, experimenting, learning, and implementing innovative solutions
- A flat, collegial work environment, with a work hard, play hard attitude
- A platform for rapid growth if you are willing to try new things without fear of failure.
- Remuneration with best-in-class industry standards with generous health insurance cover
Some of our accolades include:
- Ranked as one of America's Fastest-Growing Companies by Financial Times for five consecutive years: 2020-2024.
- Ranked as one of America's Fastest-Growing Private Companies by Inc. 5000 for seven consecutive years: 2018-2024.
- Voted #1 by more than 300 retailers worldwide in the RIS Software LeaderBoard 2024 report.
- Ranked #72 in America’s Most Innovative Companies list in 2023—by Fortune—alongside companies like Microsoft, Tesla, Apple, IBM, etc.
- Forged a strategic partnership with Google to equip retailers with cutting-edge generative AI tools.
- Recognized in multiple Gartner reports, including Market Guides and Hype Cycle, spanning assortments, merchandising, forecasting, algorithmic retailing, and Unified Price, Promotion, and Markdown Optimization Applications. Economic Times News about our funding can be accessed here.